Yingfeng Chen

2.8k total citations · 1 hit paper
30 papers, 1.1k citations indexed

About

Yingfeng Chen is a scholar working on Artificial Intelligence, Molecular Biology and Economics and Econometrics. According to data from OpenAlex, Yingfeng Chen has authored 30 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 5 papers in Molecular Biology and 4 papers in Economics and Econometrics. Recurrent topics in Yingfeng Chen's work include Reinforcement Learning in Robotics (16 papers), Artificial Intelligence in Games (6 papers) and Adversarial Robustness in Machine Learning (3 papers). Yingfeng Chen is often cited by papers focused on Reinforcement Learning in Robotics (16 papers), Artificial Intelligence in Games (6 papers) and Adversarial Robustness in Machine Learning (3 papers). Yingfeng Chen collaborates with scholars based in China, United States and Singapore. Yingfeng Chen's co-authors include Craig E. Cameron, Kevin D. Raney, Changjie Fan, Jianye Hao, Luyun Huang, Noel T. Mueller, Scott T. Kelley, Varykina G. Thackray, Ruth E. Ley and Suresh D. Sharma and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Biochemistry.

In The Last Decade

Yingfeng Chen

28 papers receiving 1.1k citations

Hit Papers

Age- and Sex-Dependent Patterns of Gut Microbial Diversit... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yingfeng Chen China 13 476 223 186 181 102 30 1.1k
R. Sujatha India 23 283 0.6× 72 0.3× 284 1.5× 155 0.9× 19 0.2× 93 2.3k
Joonsoo Park South Korea 24 337 0.7× 28 0.1× 190 1.0× 218 1.2× 48 0.5× 140 1.8k
David Jackson United Kingdom 23 599 1.3× 15 0.1× 62 0.3× 250 1.4× 15 0.1× 89 1.9k
Jair Minoro Abe Brazil 16 67 0.1× 84 0.4× 173 0.9× 52 0.3× 52 0.5× 108 766
Lucy Lu Wang United States 19 292 0.6× 15 0.1× 523 2.8× 56 0.3× 92 0.9× 68 1.2k
Xin Lai China 27 1.1k 2.3× 24 0.1× 50 0.3× 128 0.7× 71 0.7× 101 2.2k
Mingyuan Li China 18 289 0.6× 35 0.2× 99 0.5× 136 0.8× 39 0.4× 87 1.3k
Ping Shi China 22 221 0.5× 21 0.1× 82 0.4× 94 0.5× 98 1.0× 72 1.6k
Charlotte James United Kingdom 9 111 0.2× 30 0.1× 56 0.3× 529 2.9× 48 0.5× 20 1.4k
Sourish Ghosh India 15 369 0.8× 20 0.1× 59 0.3× 243 1.3× 45 0.4× 33 1.3k

Countries citing papers authored by Yingfeng Chen

Since Specialization
Citations

This map shows the geographic impact of Yingfeng Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yingfeng Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingfeng Chen more than expected).

Fields of papers citing papers by Yingfeng Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yingfeng Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yingfeng Chen. The network helps show where Yingfeng Chen may publish in the future.

Co-authorship network of co-authors of Yingfeng Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Yingfeng Chen. A scholar is included among the top collaborators of Yingfeng Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yingfeng Chen. Yingfeng Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Minxia, Wei Yang, Yingxu Wu, et al.. (2025). Evaluating the impacts of drilling and extraction activities on the marine carbonate system in the natural gas fields of Beibu Gulf, Northern South China Sea. Marine Environmental Research. 207. 107058–107058. 2 indexed citations
2.
Yang, Wei, Pei‐Zhi Zhuang, Wei Deng, et al.. (2025). Regulation of air-sea CO2 flux and aragonite saturation state in coral reef ecosystems along the eastern coast of Hainan Island, China. Marine Pollution Bulletin. 222(Pt 3). 118862–118862.
3.
Yang, Tianpei, Weixun Wang, Jianye Hao, et al.. (2023). ASN: action semantics network for multiagent reinforcement learning. Autonomous Agents and Multi-Agent Systems. 37(2). 3 indexed citations
4.
Su, Chi‐Wei, et al.. (2022). Can the green bond market enter a new era under the fluctuation of oil price?. Economic Research-Ekonomska Istraživanja. 36(1). 536–561. 59 indexed citations
5.
Zhang, Wenqi, Peng Li, Xiao Xiang Zhu, et al.. (2022). A Closed-Loop Perception, Decision-Making and Reasoning Mechanism for Human-Like Navigation. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 4717–4724. 3 indexed citations
6.
Li, Zhuo, et al.. (2022). GBGallery : A benchmark and framework for game testing. Empirical Software Engineering. 27(6). 6 indexed citations
7.
Liu, Xiangyu, Ying Wen, Yaodong Yang, et al.. (2021). Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games. Neural Information Processing Systems. 34. 6 indexed citations
8.
Yang, Tianpei, Jianye Hao, Weixun Wang, et al.. (2021). Transfer among Agents: An Efficient Multiagent Transfer Learning Framework. 3 indexed citations
9.
Wang, Meng, et al.. (2021). Reward-Constrained Behavior Cloning. 3169–3175. 4 indexed citations
10.
Hu, Yujing, Weixun Wang, Yixiang Wang, et al.. (2020). Learning to Utilize Shaping Rewards: A New Approach of Reward Shaping. arXiv (Cornell University). 33. 15931–15941. 2 indexed citations
11.
Chen, Yingfeng, et al.. (2020). Mastering Basketball With Deep Reinforcement Learning: An Integrated Curriculum Training Approach. 1872–1874. 3 indexed citations
12.
Yang, Yaodong, Jianye Hao, Guangyong Chen, et al.. (2020). Q-value Path Decomposition for Deep Multiagent Reinforcement Learning. 1. 10706–10715. 3 indexed citations
13.
Song, Yan, Yingfeng Chen, Yujing Hu, & Changjie Fan. (2020). Exploring Unknown States with Action Balance. 184–191. 4 indexed citations
14.
Chen, Yingfeng, et al.. (2020). Reinforced Evolutionary Algorithms for Game Difficulty Control. 1–7. 3 indexed citations
15.
Cuesta‐Zuluaga, Jacobo de la, Scott T. Kelley, Yingfeng Chen, et al.. (2019). Age- and Sex-Dependent Patterns of Gut Microbial Diversity in Human Adults. mSystems. 4(4). 270 indexed citations breakdown →
16.
Liu, Yong, Yujing Hu, Yang Gao, Yingfeng Chen, & Changjie Fan. (2019). Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns. 457–463. 18 indexed citations
17.
Tang, Hongyao, Jianye Hao, Tangjie Lv, et al.. (2018). Hierarchical Deep Multiagent Reinforcement Learning. arXiv (Cornell University). 9 indexed citations
18.
Jiang, Xinya, Yaqin Chai, Ruo Yuan, et al.. (2013). An ultrasensitive luminol cathodic electrochemiluminescence immunosensor based on glucose oxidase and nanocomposites: Graphene–carbon nanotubes and gold-platinum alloy. Analytica Chimica Acta. 783. 49–55. 41 indexed citations
19.
Tackett, Alan J., Yingfeng Chen, Craig E. Cameron, & Kevin D. Raney. (2005). Multiple Full-length NS3 Molecules Are Required for Optimal Unwinding of Oligonucleotide DNA in Vitro. Journal of Biological Chemistry. 280(11). 10797–10806. 55 indexed citations
20.
Huang, Luyun, Jungwook Hwang, Suresh D. Sharma, et al.. (2005). Hepatitis C Virus Nonstructural Protein 5A (NS5A) Is an RNA-binding Protein. Journal of Biological Chemistry. 280(43). 36417–36428. 203 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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